Regression modeling of solid mottle in coated papers

Abstract

The print industry has observed an exponential growth over the last decade. A shift from plastics to paper has been observed in the packaging industry due to its sustainability. The gravure process dominates the packaging industry because of long runs and high print precision. This work focuses on the effect of gravure process parameters on print mottle for 50 GSM (gram/square meters) and 65 GSM (gram/square meters) C1S (coated-one-side) paper. Solid mottle refers to unevenness in print density and occurs due to variations in substrate, ink, and process parameters degrading the print quality, thereby resulting in printed wastage and loss to an organization. The intricate mechanism of ink transfer in the gravure process needs to be studied in depth so as to deliver higher yield and lower print waste. The Stochastic Frequency Distribution Analysis (SFDA) algorithm was used to measure the print mottle. The design of experiments (DOE) was run for gravure process parameters such as line screen, viscosity, press speed, electrostatic assist (ESA) voltage, and air gap (distance between impression roller and charge bar) at varying levels. The experimental data were analyzed through analysis of variance (ANOVA), main plot, and interaction plot. The analysis revealed significance of all process parameters for minimization of solid mottle. The optimized settings showed reduction in solid mottle by 64.68% and 67.78% for 50 GSM and 65 GSM, respectively. A stepwise regression model was developed to predict the print mottle that showed correlation coefficient of 0.912 and 0.938 for 50 GSM and 65 GSM C1S papers. This work could serve as a framework to maintain operating levels of gravure process for minimization of solid mottle.